Lyes Khacef
Centre national de la recherche scientifique
25 Papers
30 Citations
Lyes Khacef is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Computer science & Neuromorphic engineering. The author has an hindex of 5, co-authored 18 publications. Previous affiliations of Lyes Khacef include University of Groningen.
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Papers
Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic Computing
Enea Ceolini,Charlotte Frenkel,Charlotte Frenkel,Sumit Bam Shrestha,Gemma Taverni,Lyes Khacef,Melika Payvand,Elisa Donati +7 more
TL;DR: This paper presents a fully neuromorphic sensor fusion approach for hand-gesture recognition comprised of an event-based vision sensor and three different neuromorphic processors, and designed specific spiking neural networks for sensor fusion that showed classification accuracy comparable to the software baseline.
Confronting machine-learning with neuroscience for neuromorphic architectures design
Lyes Khacef,Nassim Abderrahmane,Benoit Miramond +2 more
- 08 Jul 2018
TL;DR: This work implements two models of artificial neural networks coming from two different scientific domains: the multi- layer perceptron derived from machine learning and the spiking neural network inspired from neuroscience to find out the most attractive architecture for the design of embedded artificial intelligence.
Braille letter reading: A benchmark for spatio-temporal pattern recognition on neuromorphic hardware
Simon F Muller-Cleve,Vittorio Fra,Lyes Khacef,Alejandro Pequeno-Zurro,Daniel Klepatsch,Evelina Forno,D. Gigena Ivanovich,Shavika Rastogi,Gianvito Urgese,Friedemann Zenke,Chiara Bartolozzi +10 more
TL;DR: This work proposes a new benchmark for tactile sensing and highlights the challenges and opportunities of event-based encoding, neuromorphic hardware, and spike-based computing for spatio-temporal pattern recognition at the edge.
Improving Self-Organizing Maps with Unsupervised Feature Extraction
Lyes Khacef,Laurent Rodriguez,Benoit Miramond +2 more
- 18 Nov 2020
TL;DR: This work proposes to improve the SOM performance by using extracted features instead of raw data, and improves the SOM classification by +6.09\% and reach state-of-the-art performance on unsupervised image classification.
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Sensor fusion using EMG and vision for hand gesture classification in mobile applications
Enea Ceolini,Gemma Taverni,Lyes Khacef,Melika Payvand,Elisa Donati +4 more
- 01 Jan 2019
TL;DR: A framework that allows the integration of multi-sensors, EMG and visual information, to perform sensor fusion and to improve the accuracy of hand gesture recognition tasks is implemented.